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53 How to Organise Cancer Research
european journal of cancer 48, suppl. 5 (2012) S13–S19
available at www.sciencedirect.com
journal homepage: www.ejcancer.info
Monday 9 July 2012 Monday 9 July 2012
08:00−08:50
Educational Lectures 50 The Rise of Bioinformatics in Data-driven Cancer Research P. Bork1 . 1 European Molecular Biology Laboratory, Heidelberg, Germany The development of computational tools and databases started already in the 70s, mostly for sequence and structural analysis. The advent of the personal computer enabled propagation in the 80s with a further boost provided by the internet in the early 90s. With an increasing ’omics’ mindset during the 1990’s, the field increased and diversified considerably, a tendency that still holds today, amplified by the exponentially increasing amounts of data that are being generated in biology and medicine. With respect to cancer, early bioinformatics contributions were the prediction of function for cancer genes, analysis of GWAS and transcription data as well as network analysis. Currently NGS data revolutionize cancer research and are essentially relying on data handling and digestion with an increasing network modeling component. Diverse data types are currently been explored for biomarker detection from blood to stool, with the hope for early diagnosis or prognosis and eventually better treatment. Here I introduce into some of the concepts, tools and resources in Bioinformatics and will illustrate this with current research utilizing the human microbiome for biomarker discovery. 51 Statistical Challenges in the Development of Reliable and Clinically Meaningful Biomarkers L. McShane1 . 1 U.S. National Cancer Institute, Biometric Research Branch, Division of Cancer Treatment and Diagnosis A better understanding of tumor biology through identification of specific biological characteristics of tumor and host that predict tumor behavior and responsiveness to therapy will be essential for the discovery of new therapies and for optimization of cancer care for individual patients. Although thousands of correlative studies relating individual biomarkers or high-dimensional biomarker profiles to clinical characteristics or clinical outcome have been published, only rarely have these findings led to clinically useful biomarkerbased tools. Many correlative studies are conducted without clearly specified hypotheses, have poor statistical designs, use assays that are not standardized or lack reproducibility, and often employ inappropriate or misleading statistical analysis approaches. Common statistical problems include underpowered studies or overly optimistic reporting of effect sizes and significance levels due to multiple testing, subset analyses, cutpoint optimization, and model overfitting. For studies aiming to a assess a biomarker’s ability to guide treatment decisions, the importance of appropriate control groups and the potential for confounding of prognostic and predictive effects have been underappreciated. Compounding these problems, many correlative studies have not been reported in a rigorous fashion, and published articles often lack sufficient information to allow adequate assessment of the quality of the study or the generalizability of the results. Suggestions are provided for how to avoid some of the common statistical pitfalls, how to identify problematic studies, and how to report correlative studies to maximize the interpretability and usefulness of the results. 52 The use of Metabolomics to Discover Novel Metabolic Networks and new Targets for Cancer Treatment E. Gottlieb1 . 1 Cancer Research UK Beatson Institute for Cancer Research, Apoptosis and Tumour Metabolism Laboratory, Glasgow, United Kingdom The extent to which metabolism plays a role in tumorigenesis cannot be overstated and drugs that selectively target these processes are likely to at least delay, if not halt tumour progression. Our work utilizes analytical chemistry and system biology approaches to study metabolic transformation.
We investigated cells deficient in the mitochondrial tumour suppressor fumarate hydratase (FH) and using extensive metabolomics data we applied a computer model, generated to study their unique metabolome. We identified several important metabolic pathways which are specific and crucial for the survival of cancer cells deficient in FH. These include the heme biosynthesis and degradation pathway as well as mechanisms of alleviating tricarboxylic acid (TCA) cycle carbon stress. These technologies are not only important for understanding the basic biochemistry of cancer cells but they can inform us on future clinical management of cancer and may lead to new therapeutic approaches to target cancer-specific metabolic pathways.
Monday 9 July 2012
09:00−09:45
Meet the Expert 53 How to Organise Cancer Research N. Jones1 . 1 Paterson Institute for Cancer Research, Manchester, United Kingdom We are clearly in a new era of cancer research based on an explosion of knowledge on the underlying mechanisms of cancer initiation and development and on the huge and impressive advances in technologies such as DNA sequencing. The opportunities to advance a more personalised approach to cancer treatment are therefore significant but to take advantage of these opportunities the manner in which research is organised is crucial. It needs to embrace a multi-directional, multi-disciplinary integration of research activities that facilitates the interface between the biologists and the multitude of disciplines necessary for translational and clinical application. Cancer Research UK (CR-UK) is the world’s biggest cancer charity and the predominant funder of cancer research in the UK. It supports research across the entire base to clinical research spectrum with a rigid focus on advancing the personalised medicine agenda. How CR-UK organises its research activities and the different funding mechanisms it employs to support this agenda will be outlined and discussed. 54 Functional Imaging M. Schwaiger1 , A. Beer1 , S. Ziegler1 , H.J. Wester2 . 1 Klinikum rechts ¨ Munchen, der Isar − Technische Universitat ¨ Nuklearmedizinische Klinik ¨ fur ¨ Chemie, Lehrstuhl fur ¨ und Poliklinik, Munchen, ¨ Germany, 2 Fakultat Pharmazeutische Radiochemie, Garching, Germany Molecular and functional imaging has gained increasing acceptance for the in-vivo tissue characterization in patients with cancer. Using multimodal cross sectional imaging, not only anatomy and structural changes occurring in patients with cancer can be defined with high spatial resolution, but also biological processes by introducing targeted radiopharmaceuticals or contrast agents for the visualization of specific biological function. PET/CT in combination with biochemical markers such as labeled glucose (Fluordeoxyglucose, FDG) or labeled amino acids (F18-fluoro-ethyl-tyrosine, FET) can identify malignant tissue with high sensitivity and specificity. Exploiting the Warburg effect, increased glycolytic rate is indicative for malignant tissue. This biochemical signal can be used not only to stage tumors but also to assess response to therapy. Several studies have shown the predictive value of FDG imaging early after onset of chemotherapy. The separation of responders and non-responders offers the opportunity to individually adjust therapeutic regimens. New markers assessing tissue proliferation may be offering increased sensitivity for early effects of drug interaction. Fluorthymidin (FLT) has been shown to correlate with tumor proliferation in many entities. It may provide prognostic value in lymphoma patients differentiating the conversion from low to high malignant grade. Labelling of markers for angiogenesis, apoptosis and hypoxia may widen the spectrum of molecular imaging in characterizing micro-environment of tumor
0959-8049/$ – see front matter © 2012 Elsevier Ltd. All rights reserved.
available at www.sciencedirect.com
journal homepage: www.ejcancer.info
Monday 9 July 2012 Monday 9 July 2012
08:00−08:50
Educational Lectures 50 The Rise of Bioinformatics in Data-driven Cancer Research P. Bork1 . 1 European Molecular Biology Laboratory, Heidelberg, Germany The development of computational tools and databases started already in the 70s, mostly for sequence and structural analysis. The advent of the personal computer enabled propagation in the 80s with a further boost provided by the internet in the early 90s. With an increasing ’omics’ mindset during the 1990’s, the field increased and diversified considerably, a tendency that still holds today, amplified by the exponentially increasing amounts of data that are being generated in biology and medicine. With respect to cancer, early bioinformatics contributions were the prediction of function for cancer genes, analysis of GWAS and transcription data as well as network analysis. Currently NGS data revolutionize cancer research and are essentially relying on data handling and digestion with an increasing network modeling component. Diverse data types are currently been explored for biomarker detection from blood to stool, with the hope for early diagnosis or prognosis and eventually better treatment. Here I introduce into some of the concepts, tools and resources in Bioinformatics and will illustrate this with current research utilizing the human microbiome for biomarker discovery. 51 Statistical Challenges in the Development of Reliable and Clinically Meaningful Biomarkers L. McShane1 . 1 U.S. National Cancer Institute, Biometric Research Branch, Division of Cancer Treatment and Diagnosis A better understanding of tumor biology through identification of specific biological characteristics of tumor and host that predict tumor behavior and responsiveness to therapy will be essential for the discovery of new therapies and for optimization of cancer care for individual patients. Although thousands of correlative studies relating individual biomarkers or high-dimensional biomarker profiles to clinical characteristics or clinical outcome have been published, only rarely have these findings led to clinically useful biomarkerbased tools. Many correlative studies are conducted without clearly specified hypotheses, have poor statistical designs, use assays that are not standardized or lack reproducibility, and often employ inappropriate or misleading statistical analysis approaches. Common statistical problems include underpowered studies or overly optimistic reporting of effect sizes and significance levels due to multiple testing, subset analyses, cutpoint optimization, and model overfitting. For studies aiming to a assess a biomarker’s ability to guide treatment decisions, the importance of appropriate control groups and the potential for confounding of prognostic and predictive effects have been underappreciated. Compounding these problems, many correlative studies have not been reported in a rigorous fashion, and published articles often lack sufficient information to allow adequate assessment of the quality of the study or the generalizability of the results. Suggestions are provided for how to avoid some of the common statistical pitfalls, how to identify problematic studies, and how to report correlative studies to maximize the interpretability and usefulness of the results. 52 The use of Metabolomics to Discover Novel Metabolic Networks and new Targets for Cancer Treatment E. Gottlieb1 . 1 Cancer Research UK Beatson Institute for Cancer Research, Apoptosis and Tumour Metabolism Laboratory, Glasgow, United Kingdom The extent to which metabolism plays a role in tumorigenesis cannot be overstated and drugs that selectively target these processes are likely to at least delay, if not halt tumour progression. Our work utilizes analytical chemistry and system biology approaches to study metabolic transformation.
We investigated cells deficient in the mitochondrial tumour suppressor fumarate hydratase (FH) and using extensive metabolomics data we applied a computer model, generated to study their unique metabolome. We identified several important metabolic pathways which are specific and crucial for the survival of cancer cells deficient in FH. These include the heme biosynthesis and degradation pathway as well as mechanisms of alleviating tricarboxylic acid (TCA) cycle carbon stress. These technologies are not only important for understanding the basic biochemistry of cancer cells but they can inform us on future clinical management of cancer and may lead to new therapeutic approaches to target cancer-specific metabolic pathways.
Monday 9 July 2012
09:00−09:45
Meet the Expert 53 How to Organise Cancer Research N. Jones1 . 1 Paterson Institute for Cancer Research, Manchester, United Kingdom We are clearly in a new era of cancer research based on an explosion of knowledge on the underlying mechanisms of cancer initiation and development and on the huge and impressive advances in technologies such as DNA sequencing. The opportunities to advance a more personalised approach to cancer treatment are therefore significant but to take advantage of these opportunities the manner in which research is organised is crucial. It needs to embrace a multi-directional, multi-disciplinary integration of research activities that facilitates the interface between the biologists and the multitude of disciplines necessary for translational and clinical application. Cancer Research UK (CR-UK) is the world’s biggest cancer charity and the predominant funder of cancer research in the UK. It supports research across the entire base to clinical research spectrum with a rigid focus on advancing the personalised medicine agenda. How CR-UK organises its research activities and the different funding mechanisms it employs to support this agenda will be outlined and discussed. 54 Functional Imaging M. Schwaiger1 , A. Beer1 , S. Ziegler1 , H.J. Wester2 . 1 Klinikum rechts ¨ Munchen, der Isar − Technische Universitat ¨ Nuklearmedizinische Klinik ¨ fur ¨ Chemie, Lehrstuhl fur ¨ und Poliklinik, Munchen, ¨ Germany, 2 Fakultat Pharmazeutische Radiochemie, Garching, Germany Molecular and functional imaging has gained increasing acceptance for the in-vivo tissue characterization in patients with cancer. Using multimodal cross sectional imaging, not only anatomy and structural changes occurring in patients with cancer can be defined with high spatial resolution, but also biological processes by introducing targeted radiopharmaceuticals or contrast agents for the visualization of specific biological function. PET/CT in combination with biochemical markers such as labeled glucose (Fluordeoxyglucose, FDG) or labeled amino acids (F18-fluoro-ethyl-tyrosine, FET) can identify malignant tissue with high sensitivity and specificity. Exploiting the Warburg effect, increased glycolytic rate is indicative for malignant tissue. This biochemical signal can be used not only to stage tumors but also to assess response to therapy. Several studies have shown the predictive value of FDG imaging early after onset of chemotherapy. The separation of responders and non-responders offers the opportunity to individually adjust therapeutic regimens. New markers assessing tissue proliferation may be offering increased sensitivity for early effects of drug interaction. Fluorthymidin (FLT) has been shown to correlate with tumor proliferation in many entities. It may provide prognostic value in lymphoma patients differentiating the conversion from low to high malignant grade. Labelling of markers for angiogenesis, apoptosis and hypoxia may widen the spectrum of molecular imaging in characterizing micro-environment of tumor
0959-8049/$ – see front matter © 2012 Elsevier Ltd. All rights reserved.